Intelligenza Artificiale

We introduce the special issue on Evolutionary Computation (EC) reporting a non-exhaustive list of topics which have recently attracted much interest from the EC community, with particular regard to the ones dealt with by the papers included in this issue: EC research, hybrid neuro-evolutionary systems and synergies between EC and complex systems. In addition, we introduce a more technological emerging topic: the parallel implementation of evolutionary and Swarm Intelligence algorithms on graphics processor units (GPUs), by which new applications of evolutionary algorithms have been made possible, even in real-time environments.

Neuro-genetic systems have become a very important topic of study in evolutionary computation in recent years. They are models that use evolutionary algorithms to optimize neural network design. This article is a survey of the state of art of evolutionary ANN systems, with a focus on the most recent developments, presented in the literature during the last decade. The main purpose of this work is to provide an update and extension of Yao's milestone survey, published back in 1999, by taking the most recent literature into account.

In this work we demonstrate in two different contexts how we can introduce recent discoveries and technological advances into existing computational models. In the first case, we worked on improving the performance of a simple paradigm for distributed computation: cellular automata. This was achieved by applying principles inspired by Darwinian evolution to alter the connections between the cells of the system, hence changing its topological structure. We have studied the performance of these evolved structures on prototypical problems, and analyzed their response to probabilistic transient faults and permanent failures. In the second case, we consider the context of biological genetic regulatory networks and in particular a model thereof proposed by Kaufmann in the late 60's: random Boolean networks. Since the model was developed, biology has made tremendous progress and these new discoveries can be used to improve the original model. From the structure of the network, to timing of the event taking place on it, to the specifics of the genes' activation, we have added a great deal of modern knowledge into the original model, studying , analyzing, and validating it on biological case studies.

Geometric crossovers are a class of representation-independent search operators for evolutionary algorithms that are well-defined once a notion of distance over a solution space is defined. In this paper we explore the specialisation of geometric crossovers to the permutation representation analysing the consequences of the availability of more than one notion of distance. Also, we study the relations among distances and build a rational picture in which pre-existing recombination operators for permutations fit naturally. Lastly, we illustrate the application of geometric crossover to the Travelling Salesman Problem (TSP).

In this paper we overview our recent research activity concerning the induction of Logic Programming specifications, and the proof of their properties via Abductive Logic Programming. Both the inductive and abductive tools here briefly described have been applied to respectively learn and verify (properties of) interaction protocols in multi-agent systems, Web service choreographies, careflows and business processes.

In this paper we briefly describe the research activity that we have been carrying out during the last years on dynamic logic programs. After reviewing our contributions to strengthening the semantic foundations of dynamic logic programs, we describe a simple formalism to reason about actions – based on dynamic logic programs – and its event-condition-action extension that supports the specification and the execution of reactive programs.

The specification of interaction and of the related forms of reasoning is crucial in the research area of multi-agent systems and in many application areas. This article summarizes the activities and the achievements obtained by the authors in the last years. Two are the main research lines, respectively leading to the proposal of a mentalistic approach to the specification of agent interaction policies, based on the class of grammar logics, and the proposal of a constraint-based representation of regulative and declarative patterns of interaction inside commitment-based protocols.

We provide a new decidability proof for the consistency of FDNC programs under the stable model semantics, based on regular splitting sequences. With this technique, we can slightly relax the definition of FDNC programs and make a first step towards a precise understanding of the relationships between FDNC programs and finitely recursive programs.

In this paper, we briefly describe our experience in the field of analysis and transformation of logic programs. Although now we work in completely different fields, verification of security properties on the one hand and biosystems analysis on the other, our previous experience continues to be a valuable guide.

In this article we survey our recent research activity concerning the use of logic programming, and in particular of abduction, for interaction specification and verification in several domains. We outline relevant results in the areas of multi-agent systems, argumentation, web services choreographies and business processes.

In this paper, we briefly describe recent research directions of the Artificial Intelligence group of the University of L'Aquila, Italy. Research activities concern Computational Logic and Artificial Intelligence. About Intelligent Logical Agents, in the last years the group has developed the logical agent-oriented language DALI. Work is under way also in other areas, namely, Non-Monotonic Reasoning and Natural Language Processing. We particularly emphasize recent and future work directions.

In this paper, we summarize the contribution of our research group to the field of Bioinformatics. In particular, we present our approach to the ab-initio solution of the protein structure prediction problem based on constraint/logic programming techniques.

This paper briefly describes the use of the program transformation methodology for the development of correct and efficient programs. In particular, we will refer to the case of constraint logic programs and, through some examples, we will show how by program transformation, one can improve, synthesize, and verify programs.

We briefly outline our research activity, started in the 90s, in the field of non-classical logics. In particular, we describe our activity on the use of non-classical logics for knowledge representation and on proof methods for non-monotonic and conditional logics.

In this paper, we describe the research lines in logic programming, carried out in Cosenza over a period of more than twenty years, which have recently produced promising industrial exploitation follow-ups. The research lines have changed over the time but they have kept the initial interest on combining logic programming with databases techniques, that has been continuously renewed to cope with new challenges, in our attempt to use theory to solve practical problems.

We describe recent work on the deployment of computational logic to support the formalisation and implementation of agents in multi-agent systems. Several forms of computational logic systems are needed in this setting, including abductive, argumentative and preference-based systems. We briefly sketch the agent model called KGP, and an ongoing extension of it which is needed to model agents in distributed settings such as the Grid and, more generally, Service-Oriented Architectures.

Computational Logic plays a very relevant role in engineering complex systems. It can be used to specify systems at different levels of abstraction. The specifications are executable, thus providing a working prototype for free. Thanks to its well-founded semantics it can be used to reason about the correctness of the specifications, a fundamental aspect when safety critical applications are developed. Researchers working in the Logic Programming Group at DISI, a Genova University Department, have applied methods and tools of Computational Logic for modelling, prototyping, and verifying complex systems. These three research lines are largely overlapping: the complex systems we take into account are often multiagent systems, for which we propose modelling languages as well as prototyping environments and verification techniques. In this paper we describe activities that, in the last decade, we carried out along these research lines.

Despite the popularity of the World Wide Web as a development platform, a proper description of its architectural principles and design criteria has been established only in the last decade, by the introduction of the REpresentational State Transfer (REST) architectural style, which defines the resource as the key abstraction of information. Languages and tools used for Web programming generally suffer from a lack of proper understanding of its architecture and design constraints, and from an abstraction mismatch that makes it hard to fully exploit the Web potential. Declarative languages are well-suited for a programming system aimed at being respectful of the Web architecture and principles. Among logic technologies, tuProlog has been explicitly designed to be one of the enabling components of Internet-based infrastructures: its engineering properties make it suitable for use on the Web, where logic programming allows modification of resource behaviour at runtime. Accordingly, in this paper we present a Prolog-based logic model for programming Web resources, and outline a framework for developing Web applications grounded on that model.

In this paper, we briefly summarize some of the most challenging issues that arise when allowing sets to be dealt with as first-class objects of a logic language, ranging from unification of well-founded and non-well-founded sets, to set constraint solving.